Auto Exposure Algorithm Frame Rate Initialization
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Solution Overview
Problem
Existing camera systems face challenges in power consumption and transition delays when switching from sleep mode to operational mode, particularly in mobile devices, due to inefficient auto exposure methods that always start with a low frame rate regardless of ambient light conditions.
Innovation Solution
An auto exposure method for image capture devices that uses an ambient light sensor to select a frame rate corresponding to ambient light data, initializing an auto exposure algorithm to determine optimal image capture parameters such as sensor gain and exposure time, allowing for faster convergence and reduced power consumption by adapting frame rates based on light conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the camera system uses a fixed low frame rate for auto exposure regardless of ambient light conditions, then power consumption is reduced, but the convergence speed of the auto exposure algorithm is slowed down
Solution Approach 1:
The patent implements dynamic frame rate adjustment based on ambient light conditions. The system transitions from a fixed low frame rate to a variable frame rate that adapts to lighting conditions, using higher frame rates in bright light and lower frame rates in dim light, thereby resolving the contradiction between power consumption and convergence speed
Solution Approach 2:
The patent changes the operational parameters of the auto exposure algorithm by adjusting the frame rate according to ambient light measurements. This parameter adaptation allows the system to optimize both power consumption and convergence speed by matching the frame rate to the actual lighting conditions rather than using a fixed rate
2Ease of operation
If the camera system transitions from deep sleep mode to operational mode, then image capture functionality is restored, but transition delays occur
Solution Approach 1:
The patent performs preliminary actions during the transition from sleep mode by pre-calculating or pre-loading certain parameters based on ambient light sensor data that may have been captured before sleep mode engagement. This preliminary preparation reduces the time required to achieve operational readiness
3Loss of energy
If the auto exposure algorithm always starts with a low frame rate, then power consumption is minimized, but boot-to-capture time is increased
Solution Approach 1:
The system dynamically adjusts the frame rate during the boot-to-capture sequence based on ambient light conditions. Instead of always starting with a low frame rate, the system selects an appropriate initial frame rate that balances power consumption with the need for quick capture readiness, thereby reducing overall boot-to-capture time
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach results in faster convergence of the auto exposure algorithm, reducing boot-to-capture time by 20% and achieving 50% faster convergence in mid-light and 75% faster in bright light conditions compared to conventional systems, while optimizing power usage.
Implementation Method 1
gathering ambient light data with an ambient light sensor of the image capture device
Data Source
AI summary
Imaging methods and imagers for image capture devices. Still images are captured by gathering ambient light data using an ambient light sensor of the image capture device, selecting a frame rate for the imager corresponding to the gathered ambient light data, determining optimal image capture parameters for the imager by executing an auto exposure algorithm with a processor using the selected frame rate as an initialization parameter for the auto exposure algorithm, and capturing a still image with the imager after execution of the auto exposure algorithm using the selected frame rate.